Simulation and Analysis of Flexible Solar Panels' Deployment and Locking Processes

To predict the attitude of satellite during the whole deployment process and evaluate the locking impact, a numerical flexible model of a certain satellite associated with four flexible honeycomb solar panels was established. The flexible solar panel was modeled by the finite element analysis (FEA), and the motion equations were derived by Lagrangian formulation. The locking process was based on the method of Hertzian contact, which enables one to predict the locking impact on the satellite and the subsequent oscillation of solar panels. The results reveal that locking operation has great impact on the attitude of the satellite, and the angular acceleration of satellite reaches 22.03°/s2 at the locking moment; the flexible solar panels model is feasible to predict the accurate response of the satellite during deployment and the oscillation of solar panels; the instantly impulsive force occurred during locking process is about 1.5 kN and the changing time is nearly 0.32 s. It provides an effective approach to present the flexible solar panels' deployment process and evaluate the locking impact.

Dynamic modeling of spacecraft solar panels deployment with Lie group variational integrator

The spacecraft with multistage solar panels have nonlinear coupling between attitudes of central body and solar panels, especially the rotation of central body is considered in space. The dynamics model is based for dynamics analysis and control, and the multistage solar panels means the dynamics modeling will be very complex. In this research, the Lie group variational integrator method is introduced, and the dynamics model of spacecraft with solar panels that connects together by flexible joints is built. The most obvious character of this method is that the attitudes of central body and solar panels are all described by three-dimensional attitude matrix. The dynamics models of spacecraft with one and three solar panels are established and simulated. The study shows Lie group variational integrator method avoids parameters coupling and effectively reduces difficulty of modeling. The obtained continuous dynamics model based on Lie group is a set of ordinary differential equations and equivalent with traditional dynamics model that offers a basis for the geometry control.

Dimension of Solar Panels Surface Based to the Net Present Value for the Albanian Conditions

Active exploitation of solar energy is achieved in systems that absorb this energy through flat collectors. Hot water can be used for space heating, when its temperature is high, but it is used largely for DHW （domestic hot water） needs. Now days, this technology has resulted as the most viable for exploitation of solar energy, and various countries such as Israel, Turkey, and Greece provide hot water for residential and service sectors using systems of solar panels. In this proceeding we are writing about the dimension of the solar panels surface based to the net present value in Hotels of Albania.

Quasi-Horizontal Arrangement of Solar Panels in Equatorial Zones： Problems and Proposed Solutions

Solar panels are oriented to the North （South） when the site is in the South （North） with a tilt angle close to the latitude. In the equatorial zone, the panels are quasi-horizontally arranged. This situation caused some problems： the panel is more rapidly covered with dust or salty mud that decreases its performance and degrades the protective glass. To overcome these difficulties, we evaluated theoretically and practically the energy lost by an incorrect tilt. The results are rather encouraging. Just 1.5% of total energy is lost when we tilted the panel at 10.0°. In practice, we realized that the loss of energy is fewer than we calculated it because of the reflected solar rays.

Dynamic analysis of tethered defunct satellites with solar panels

A precise dynamic model for towing and removing a defunct satellite with solar panels in orbit using a tethered net often has low computational efficiency owing to the complex contact and collision between the net and panels,which is not conducive to research.To solve this problem,a“single main tether–multiple subtether”bifurcation structure with beads was employed as the tethered net model.This study investigated the dynamics of tethered defunct satellites with solar panels,particularly the behavior of the attitude of the tethered satellite,oscillation of the main tether,and vibration of solar panels under different conditions.The results showed that different attachment configurations of the subtethers and the flexibility of the main tether have an evident impact on the dynamic characteristics of the system.

Vibration control for the solar panels of spacecraft: Innovation methods and potential approaches

Solar panels on spacecraft are typical kinds of flexible structures.Low‐frequency and large‐amplitude vibrations usually occur due to the inevitable disturbances of deployment impact,attitude/orbit maneuver,separation/docking impact,and so forth.These vibrations degrade the stability of the spacecraft platform,leading to a reduction in imaging quality and pointing direction accuracy.Vibration control is obligatory during flight missions.Here,we summarize the researches on vibration control of the solar panels.First,typical solar panels used in spacecraft and the specific difficulties in dynamic modeling and control design are introduced.Next,the researches on dynamic modeling methods,decentralized vibration control strategy,and in‐orbit vibration controller design technologies are presented sequentially.Finally,a practical example where our method was successfully applied in‐orbit is described.In conclusion,the theories,methods,and technologies presented in this review hold significant value for achieving high‐precision performance in large spacecraft.

Smart Monitoring of Solar Photovoltaic Panels by the Approach of Machine Learning

The exploitation of renewable energy has become a pressing task due to climate change and the recent energy crisis caused by regional conflicts.This has further accelerated the rapid development of the global photovoltaic(PV)market,thereby making the management and maintenance of solar photovoltaic(SPV)panels a new area of business as neglecting it may lead to significant financial losses and failure to combat climate change and the energy crisis.SPV panels face many risks that may degrade their power generation performance,damage their structures,or even cause the complete loss of their power generation capacity during their long service life.It is hoped that these problems can be identified and resolved as soon as possible.However,this is a challenging task as a solar power plant(SPP)may contain hundreds even thousands of SPV panels.To provide a potential solution for this issue,a smart drone-based SPV panel condition monitoring(CM)technique has been studied in this paper.In the study,the U-Net neural network(UNNN),which is ideal for undertaking image segmentation tasks and good at handling small sample size problem,is adopted to automatically create mask images from the collected true color thermal infrared images.The support vector machine(SVM),which performs very well in highdimensional feature spaces and is therefore good at image recognition,is employed to classifying the mask images generated by the UNNN.The research result has shown that with the aid of the UNNN and SVM,the thermal infrared images that are remotely collected by drones from SPPs can be automatically and effectively processed,analyzed,and classified with reasonable accuracy(over 80%).Particularly,the mask images produced by the trained UNNN,which contain less interference items than true color thermal infrared images,significantly benefit the assessing accuracy of the health state of SPV panels.It is anticipated that the technical approach presented in this paper will serve as an inspiration for the exploration of more advanced and dependable smart asset management techniques within the solar power industry.

Intelligent Solar Chasing Street Light System Design and Fabrication Summaries

This project adopts an advanced microcontroller as the core control unit,which accurately commands the servo drive,realizes the real-time light chasing and charging function of the solar panel,and effectively manages the power supply system of the street light.At the same time,the system is able to continuously monitor the operation status of the servo within the range of 0°to 180°to ensure that it is trouble-free and not offline.The hardware system construction consists of five modules:a power module,solar panel module,servo module,street light module,and Organic Light-Emitting Diode(OLED)display module.Each module works together to support the stable operation of the whole system.The system workflow is to accurately determine the direction of the light source by collecting real-time light intensity data through four precision photoresistors.Subsequently,the microcontroller intelligently controls the helm module based on these data to drive the solar panel to rotate within a range of 180°to accurately track the sun’s orientation.The street light provides two lighting modes,automatic and manual,to meet the needs of different scenarios.During the daytime,the solar panels work actively to monitor and collect solar energy efficiently in real-time,meanwhile,when night falls,the solar panels switch to standby mode and the streetlights light up automatically,illuminating the road ahead for pedestrians.Compared with the traditional solar street lights on the market,the intelligent solar light chasing road system introduced in this project has significant advantages.Its unique light-chasing algorithm enables the solar panel to continuously track the light source from sunrise to sunset,thus significantly improving the charging efficiency.Compared with traditional street lights,the biggest advantage of this project is the proposed light-chasing algorithm,which can always charge from sunrise until sunset,making the charging efficiency increase by 38%to 47%.The charging efficiency is 20%to 38%higher than that of traditional street lamps.Simultaneously,the biggest advantage of this project is that the power storage capacity is higher than 35%of the traditional solar street light.Bringing users a more durable and stable lighting experience.

Comprehensive Examination of Solar Panel Design: A Focus on Thermal Dynamics

In the 21st century, the deployment of ground-based Solar Photovoltaic (PV) Modules has seen exponential growth, driven by increasing demands for green, clean, and renewable energy sources. However, their usage is constrained by certain limitations. Notably, the efficiency of solar PV modules on the ground peaks at a maximum of 25%, and there are concerns regarding their long-term reliability, with an expected lifespan of approximately 25 years without failures. This study focuses on analyzing the thermal efficiency of PV Modules. We have investigated the temperature profile of PV Modules under varying environmental conditions, such as air velocity and ambient temperature, utilizing Computational Fluid Dynamics (CFD). This analysis is crucial as the efficiency of PV Modules is significantly impacted by changes in the temperature differential relative to the environment. Furthermore, the study highlights the effect of airflow over solar panels on their temperature. It is found that a decrease in the temperature of the PV Module increases Open Circuit Voltage, underlining the importance of thermal management in optimizing solar panel performance.

Great wall of solar panels to mitigate yellow dust storm

Mitigation of the large scale yellow dust storm is a serious problem facing China. We propose the approach of building windbreak walls equipped with solar panels in the proximity of dust origins. The solar panels generate electricity in the sunny days; the walls break the wind and remove airborne dusts based on the impactor principle during wind storms. Preliminary calculation indicates the walls may be able to remove the major fraction of the airborne dusts and the generated electricity could be significant. More detailed studies are needed to prove the feasibility of the approach.

An Automatic Dust Removal Device Based on SCM for Solar Panels

This paper introduces a set of automatic dust removal device for street lamp solar panels. The device realizes the automatic dust removal for street lamp solar panels by three steps consisting of data acquisition, automatic control and mechanical dust removal. Our scheme is as follows, according to the comparison between the actual power generation and the relatively ideal condition of power generation of solar panels, we selectively conduct dust removal operation to panels. The paper demonstrates the feasibiliW of the technology based on the example of street lamp solar panels （40w）. According to the calculation, the solar panels equipped with our device will greatly improve the power generation efficiency of solar panels, which means there will be 32 more degrees generated every year. Extension and application of the technique device will be beneficial for the improvement of solar panels power generation efficiency and the extension of the service life of the panels.

Automated Classification of Snow-Covered Solar Panel Surfaces Based on Deep Learning Approaches

Recently,the demand for renewable energy has increased due to its environmental and economic needs.Solar panels are the mainstay for dealing with solar energy and converting it into another form of usable energy.Solar panels work under suitable climatic conditions that allow the light photons to access the solar cells,as any blocking of sunlight on these cells causes a halt in the panels work and restricts the carry of these photons.Thus,the panels are unable to work under these conditions.A layer of snow forms on the solar panels due to snowfall in areas with low temperatures.Therefore,it causes an insulating layer on solar panels and the inability to produce electrical energy.The detection of snow-covered solar panels is crucial,as it allows us the opportunity to remove snow using some heating techniques more efficiently and restore the photovoltaics system to proper operation.This paper presents five deep learning models,■-16,■-19,ESNET-18,ESNET-50,and ESNET-101,which are used for the recognition and classification of solar panel images.In this paper,two different cases were applied;the first case is performed on the original dataset without trying any kind of preprocessing,and the second case is extreme climate conditions and simulated by generating motion noise.Furthermore,the dataset was replicated using the upsampling technique in order to handle the unbalancing issue.The conducted dataset is divided into three different categories,namely;all_snow,no_snow,and partial snow.The fivemodels are trained,validated,and tested on this dataset under the same conditions 60%training,20%validation,and testing 20%for both cases.The accuracy of the models has been compared and verified to distinguish and classify the processed dataset.The accuracy results in the first case showthat the comparedmodels■-16,■-19,ESNET-18,and ESNET-50 give 0.9592,while ESNET-101 gives 0.9694.In the second case,the models outperformed their counterparts in the first case by evaluating performance,where the accuracy results reached 1.00,0.9545,0.9888,1.00.and 1.00 for■-16,■-19,ESNET-18 and ESNET-50,respectively.Consequently,we conclude that the second case models outperformed their peers.

Indian Solar Panel Initiatives in Reducing Carbon Dioxide Emissions

Environmental degradation and the emission of greenhouse gases particularly carbon dioxide have expanded problems to human wellness and to the atmosphere. The second-most populated country in the globe, India, is among the primary users of conventional resources, which leads to global warming. The growth rate is anticipated to raise more before 2050, which will cause the brisk industrial expansion and rising energy demand to both increases. In order to reduce carbon emissions and meet energy requirements, many countries use alternate usage of renewable energy particularly solar energy. In this review we aim to study solar panel schemes initiated by India, mainly focusing on National Solar Mission. This study also reviews the present solar installed capacity, solar panel scheme 2022, and initiatives and outcomes of solar panels in residences and offices. This study reviewed that by using solar panel resources, the (MNRE) Ministry of New and Renewable Energy hopes to help the Indian Government reach its purpose of 100 GW solar installed capacity by end of 2022. Despite having an amazing 40 GW of solar power installed capacity till December 2021, India is still far from reaching its own goal of 100 GW by March 2023 as per NSM. In essence, this means that India will need to change a few of its ongoing plans further.

Tilt Angle Optimality Criteria for Stand Alone PV Systems

The conventional approach to optimizing tilt angles for fixed solar panels aims to maximize energy generation over the entire year. However, in the context of a supply controlled electric grid, where solar energy availability varies, this criterion may not be optimal. This study explores two alternative optimization criteria focused on maximizing baseload supply potential and minimizing required storage capacity to address seasonality in energy generation. The optimal tilt angles determined for these criteria differed significantly from the standard approach. This research highlights additional factors crucial for designing solar power systems beyond gross energy generation, essential for the global transition towards a fully renewable energy-based electric grid in the future.

Recycling waste crystalline-silicon solar cells: Application as high performance Si-based anode materials for lithium-ion batteries

Recycling useful materials such as Ag, Al, Sn, Cu and Si from waste silicon solar cell chips is a sustainable project to slow down the ever-growing amount of waste crystalline-silicon photovoltaic panels. However, the recovery cost of the above-mentioned materials from silicon chips via acid-alkaline treatments outweights the gain economically.Herein, we propose a new proof-of-concept to fabricate Si-based anodes with waste silicon chips as raw materials.Nanoparticles from waste silicon chips were prepared with the high-energy ball milling followed by introducing carbon nanotubes and N-doped carbon into the nanoparticles, which amplifies the electrochemical properties. It is explored that Al and Ag elements influenced electrochemical performance respectively. The results showed that the Al metal in the composite possesses an adverse impact on the electrochemical performance. After removing Al, the composite was confirmed to possess a pronounced durable cycling property due to the presence of Ag, resulting in significantly more superior property than the composite having both Al and Ag removed.

A Novel Integrated Photovoltaic System with a Three-Dimensional Pulsating Heat Pipe

Solar energy is a valuable renewable energy source,and photovoltaic(PV)systems are a practical approach to harnessing this energy.Nevertheless,low energy efficiency is considered a major setback of the system.Moreover,high cell temperature and reflection of solar irradiance from the panel are considered chief culprits in this regard.Employing pulsating heat pipes(PHPs)is an innovative and useful approach to improving solar panel performance.This study presents the results of the power performance of a PV panel attached to a newly designed spiral pulsating heat pipe,while graphene oxide nanofluid with three different concentrations was used as a working fluid to maximize the efficacy of the solar panel.The study proved that the cooling method delivered high efficiency by reducing the temperature,especially in the middle of the day.Using nanofluid graphene oxide at concentrations of 0.2,0.4,and 0.8 gr/lit as the working fluid can reduce the thermal resistance of PHPs by over 30%,24%,and 15%,respectively.This,in turn,enhances the system’s electrical power output by approximately 9%,7%,and 6%,respectively.

Optimised Design and Analysis of Solar Water Pumping Systems for Pakistani Conditions

This paper is about the optimized design and analysis of two solar water pumping systems in which one of the systems is designed with a battery bank and other with a cylindrical water tank for a selected site in Pakistan. The design, sizing, cost analysis and steady state analysis of the proposed systems were done in HOMER and dynamic analysis of the designed system with battery bank was performed in MATLAB/Simulink. The simulations performed in HOMER involved proper mapping of the loads which helped to evaluate the PV panel requirement, inverter rating, batteries (in case of battery based solution), modeling of water tank as a deferrable load (in case of solution based of water tank) and detailed cost analysis for a life time of 25 years. To verify the design of the solar water pumping system with battery bank, a simulation in MATLAB/Simulink for study of dynamic behavior of the overall system was performed which involved mathematical modeling of a PV panel, buckboost converter, inverter, battery bank and motor/pump, a perturb and observe maximum power point tracking algorithm based control system. Analysis was conducted based on the economic results that indicate designed solar water pumping system with water tank would be a cheaper solution as compared to solar water pumping system with a battery bank. This work can be taken as a case study for the understanding and optimized designs of solar water pumping system with battery bank and with cylindrical tank in Pakistani conditions.

Modelling of Solar Power Production in Dry and Rainy Seasons Using Some Selected Meteorological Parameters

In this paper, we deployed the multiple linear regression method in developing a solar power output model for solar energy production, where the meteorological parameters are the independent variables. We fitted the model and found that the meteorological variables considered accounted for 94.88% and 99.61% of the power output in both dry and rainy seasons. We observed from the work that the solar panel performs well in all seasons but slightly better in the rainy seasons. This could be attributed to the washing away of dust particles from solar panels by the rain and higher operating temperature different from the specified manufactured temperature of 25°C. We observed that other factors such as the cloud slightly affect the optimal performance of the system. Panels inclined at an angle of 5° (Tilt) and facing south azimuth performs optimally, periodic washing of the surface of solar panels enhances optimal performance.

Experimental Processus for Acquisition Automatic Features of I-V Properties and Temperature of the Solar Panel by Changing the Operating Point

A development of an acquisition of the characteristic of a solar panel by automatic load variation system is put into play and coupled to an instrumentation chain for taking account of temperature. A programmed digital microprocessor control enables this automation. Design and implementation of a device for automation of variations of the resistive load are powered by solar panel. It is provided by a PIC 16F877A running a computer program that we have developed on the basis of an algorithm according to the operation that we have set. By varying automatically the resistive load, we were able to automatically acquire the characteristic I-V and temperature of the solar panel. With automatic combinations of the 10 resistors, we have obtained 1024 measures of the characteristic curve of the solar cell which has a good accuracy. The change in load and temperature measurement allows us to have the characteristic curves parameterized by temperature.

Solar Power Highlights China’s Manufacturing Future

CHINA’s achievements in economic development and poverty reduction are historically unprecedented.But,it must never be forgotten from what an extremely low base China began its development in 1949 after a century of foreign invasions and wars.In 1950 only 10 countries for which there is data had lower per capita GDPs than China.